The present invention relates generally to size discrimination systems and methods, and more particularly to size discrimination systems and methods which implement nonlinear median filtering techniques.
State-of-the-art digital target identification systems utilize numerous image processing techniques to eliminate noise and unwanted clutter from images processed thereby. For example, impulse noise may be removed from a video image by means of what is referred to as a median of medians operator. This is a computer algorithm which is implemented in hardware that processes digital video signals by means of median filters.
The median of medians image processing technique is discussed in "Investigation of VLSI Technologies for Image Processing," by W. L. Eversole et al, in the Proceedings of the IEEE, Image Understanding Workshop, at page 10. A copy of that article is enclosed herewith and incorporated herein by reference. As mentioned in the paper, a video image corrupted by impulse noise was passed through circuitry which implemented the median of medians operation. As stated in the article, the filtered image removed the impulse noise, but previously sharp edges were blurred.
A second article by Eversole et al, entitled "Investigation of VLSI Technologies for Image Processing," Proceedings of the IEEE, Image Understanding Workshop, November 1978, at page 191, further discusses the use of median filtering for noise reduction purposes. As indicated in this paper, median filtering is a nonlinear signal processing technique for noise suppression in images.
The median filter comprises a sliding window encompassing an odd number of pixels. The center pixel in the window is replaced by the median of the pixels within the window. The median pixel value is that pixel value for which half of the pixel values are smaller or equal in value and half are larger or equal in value. In general, median filtering is more effective in reducing the effect of discrete impulse noises than smoothly generated noise.
In "Image Understanding Architecture," by Graham R. Nudd, in a publication by the National Computer Conference, 1980, at page 377, a wide variety of image processing techniques are discussed. In particular, the use of median filtering is mentioned as it pertains to elimination of noise spikes, and use in other statistical operations such as histogramming, variance and mode filtering.
Mention is also made of the fact that median filters may be used as a size filter, and that they are widely used as such. However, this statement is not believed to be true. A diligent search of the art relevant to size filtering indicates that, heretofore, size filtering has not been performed by means of median filters. In addition, this article does not mention how such size filtering is implemented nor is there any discussion of details regarding how this could be accomplished.
In current state-of-the-art target recognition systems, and the like, it is necessary to categorize potential targets and distinguish them from background clutter and non-target objects. Various criteria may be employed to distinguish target objects from non-targets, including size, shape, or motion-oriented attributes, or the like.
Size determination is a significant discriminant in determining the presence of potential targets located in an image scene. Determining the relative sizes of potential targets and more importantly, excluding those objects from the image which are clearly not potential targets would be very advantageous.